1

Machine Learning Engineer Software Engineer Jobs in San Jose, CA

Our direct client is hiring a Machine Learning Engineer for their software machine learning and computer vision team to design, develop, and implement critical machine learning models supporting ...

Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI ... Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ...

Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI ... Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ...

Overview Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside ... Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ...

Our direct client is hiring a Machine Learning Engineer for their software machine learning and computer vision team to design, develop, and implement critical machine learning models supporting ...

Responsibilities : โ€ข Be an early member of a high-performing team of software engineers and machine learning researchers building a new human identity platform โ€ข Take ownership, be creative, and ...

Machine Learning Engineer

San Jose, CA

$96K - $128K/yr

We are looking for a Machine Learning Engineer to join our team of driven machine learning and software engineers. This role covers system design, prompt engineering, ML model evaluation, building ...

About the Team Do you want to build AI-powered software that impacts millions of people every day ... About the Role As a Machine Learning Engineer on the AI Core team, you will develop tailored user ...

New

Machine Learning Engineer

San Jose, CA ยท On-site

$96K - $128K/yr

We are looking for a Machine Learning Engineer to join our team of driven machine learning and software engineers. This role covers system design, prompt engineering, ML model evaluation, building ...

About the Team Do you want to build AI-powered software that impacts millions of people every day ... About the Role As a Machine Learning Engineer on the AI Core team, you will develop tailored user ...

Collaborate with Data Engineers, Software Engineers, Product Managers, Clinical teams, and business ... machine learning experience. * Healthcare domain experience is mandatory -- including HIPAA ...

We are a close-knit team of highly accomplished, deeply technical research scientists, software engineers, and machine learning engineers passionate about delivering innovative technologies that ...

Collaborate with Data Engineers, Software Engineers, Product Managers, Clinical teams, and business ... machine learning experience. * Healthcare domain experience is mandatory - including HIPAA ...

Showing results 41-60

Machine Learning Engineer Software Engineer information

See San Jose, CA salary details

$74.4K

$172.9K

$240.8K

How much do machine learning engineer software engineer jobs pay per year?

As of Aug 9, 2026, the average yearly pay for machine learning engineer software engineer in San Jose, CA is $172,896.00, according to ZipRecruiter salary data. Most workers in this role earn between $140,600.00 and $202,800.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Engineer Software Engineer vs Data Scientist?

AspectMachine Learning EngineerSoftware Engineer
Required CredentialsBachelor's/Master's in CS, specialized ML coursesBachelor's in CS or related field
Work EnvironmentDevelops ML models, algorithms, data pipelinesBuilds software applications, systems, APIs
Industry UsageAI/ML projects, data-driven solutionsWeb, mobile, enterprise software

Machine Learning Engineers focus on designing and deploying ML models, requiring expertise in algorithms and data handling. Software Engineers develop broader software applications, emphasizing coding and system architecture. While both roles require programming skills, ML Engineers specialize in AI/ML tasks, whereas Software Engineers work across various software domains.

How do machine learning engineer software engineers typically collaborate with data scientists and software development teams?

Machine Learning Engineer Software Engineers often serve as a bridge between data scientists and software development teams. They work closely with data scientists to understand and implement machine learning models, ensuring that the models are production-ready and scalable. Additionally, they collaborate with software engineers to integrate these models into existing applications, monitor their performance, and address any engineering challenges. This cross-functional collaboration is essential for delivering robust, end-to-end AI solutions that add real value to the business.
What are popular job titles related to Machine Learning Engineer Software Engineer jobs in San Jose, CA? For Machine Learning Engineer Software Engineer jobs in San Jose, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Software Engineer jobs in San Jose, CA look for? The top searched job categories for Machine Learning Engineer Software Engineer jobs in San Jose, CA are:
What cities near San Jose, CA are hiring for Machine Learning Engineer Software Engineer jobs? Cities near San Jose, CA with the most Machine Learning Engineer Software Engineer job openings:
Infographic showing various Machine Learning Engineer Software Engineer job openings in San Jose, CA as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 78% In-person, and 22% Remote job distribution, with an average salary of $172,896 per year, or $83.1 per hour.

Machine Learning Engineer

Winaxis

Fremont, CA โ€ข On-site

Contractor

Re-posted 23 days ago


Job description

Title: Machine Learning Engineer

Location: Fremont, CA (Local) Onsite interview

Duration: 12+ Mos  

H1B

Only h1 candidate

About the Role:

Our direct client is hiring a Machine Learning Engineer for their software machine learning and computer vision team to design, develop, and implement critical machine learning models supporting factory and warehouse operations. You will transform ambiguous problem statements into robust end-to-end solutions using a variety of machine learning techniques and tools, including supervised learning, convolutional neural networks, and modern frameworks such as PyTorch and Pandas.

You will collaborate closely with partners in production, process, controls, and quality to deliver solutions for the most challenging problems in our operations. Your work will involve evaluating and deploying models in production environments, ensuring rapid and reliable alerting systems, and addressing operational issues as they arise. You must be adept at handling diverse, heterogeneous datasets that span multiple modalities, including images, multi-spectral sensor outputs, voice, text, and tabular data.

Responsibilities

Design, develop, and deploy machine learning models for factory and warehouse environments.

Collaborate with cross-functional teams to identify, define, and solve high-impact operational challenges.

Build and maintain end-to-end machine learning pipelines, from data collection and preprocessing to model deployment and monitoring.

Evaluate and compare models using statistical methods to ensure optimal performance and feasibility.

Ensure robust alerting and monitoring systems are in place for deployed models to address issues rapidly.

Work with diverse datasets, integrating multiple data types such as images, sensor data, voice, text, and tabular information.

Write clean, modular, and sustainable code to translate research ideas into production-ready solutions.

Minimum Requirements

In-depth knowledge of Python for high-performance, data-intensive applications.

Proficiency with at least one modern deep learning framework (e.g., PyTorch, Jax, TensorFlow).

Expertise in one or more of the following areas: computer vision, large language models, recommender systems, or operations research.

Foundational knowledge of statistics for model comparison and performance assessment.

Real-world experience deploying and maintaining machine learning solutions in production environments.

Passion for clean, sustainable, and modular code to bring research concepts to practical implementation.

Preferred Qualifications

Experience working in manufacturing, industrial automation, or warehouse environments.

Familiarity with multi-modal data integration and analysis.

Strong problem-solving skills and the ability to thrive in ambiguous, fast-paced settings.

Excellent communication skills for cross-functional teamwork.